학술논문
Bayesian Neural Network Implemented by Dynamically Programmable Noise in Vanadium Oxide
Document Type
Conference
Author
Source
2023 International Electron Devices Meeting (IEDM) Electron Devices Meeting (IEDM), 2023 International. :1-4 Dec, 2023
Subject
Language
ISSN
2156-017X
Abstract
For the first time, the dynamically programmable noise on a vanadium oxide (VO 2 ) device is extensively studied and exploited for implementing a Bayesian neural network (BNN). We demonstrate programming of noise in a VO 2 device with either resistance programming or temperature control. The VO 2 device achieved a 6.4 dynamic ratio on noise. We show that this ratio is sufficient to achieve ideal numerical levels of uncertainty quantification on CIFAR-100, achieving an expected calibration error of 3.7% (ECE measures the consistency between the network’s accuracy and uncertainty).